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少年牧尘，资质卓绝，出生于北灵境九大域之一牧域。其父为牧域域主，其母身份神秘，在牧尘年幼时被迫离开，他立下誓言，要找回母亲。他凭借天赋被审判之镜选中进入竞技历练，在历练时救了陷入困境的少女洛璃，两人产生了懵懂的感情，相约以后一起进入北苍灵院。作为北灵境独个能进入竞技的人，却在一年后因别人算计被诬陷为“灵路血祸”的凶手而被逐出比赛。不屈的牧尘机缘巧合下遇到九幽雀，获得神功。通过刻苦训练，参加学院面向牧域的海选，突破至尊境界并取得冠军，得以进入北苍灵院学习。为了救母亲，牧尘要变得更强，他与九幽雀为了寻找能让自身进步的不朽图纸，闯入精彩绝伦的大千世界，来到疆域辽阔的大罗领域。在经历腥风血雨后，牧尘救出自己的母亲，消灭了为祸人间的邪族，从草根少年成长为撼动大陆、为善除恶的大英雄，同时收获了爱情和友情 。雪上加霜的是，全军最高统帅杨宜不敢有什么主见，并且没有任何军事经验，因鬼倭游击腹地，防卫空虚，故效仿张经，从外省调兵来守，可他并没有张经那样震慑全军的威信，各路外省兵再加上狼兵混在一起，还没见到倭寇自己就先干起来了。2. Zhang LiangyingThis is the case with my neighbor Aunt Wang. Because her family's financial conditions are not very good, she especially likes to toss and turn when buying vegetables. She goes to the New Century Supermarket at the gate of the community and has a look: "Lettuce costs 3.5 yuan per catty, which is too expensive." Therefore, she took a six-stop bus to Wal-Mart, "more expensive, four dollars a kilo." Therefore, she took another seven stops to Yonghui. "Three dollars a kilo is great." She bought 5 kg and went home happily. After tossing and turning for half a day, I deducted the fare and lost 50 cents.少女傅容生于金匠世家，聪敏好学，由于目睹姐姐的不幸婚姻，遂立誓自强自立，绝不随波逐流，一定要掌控自己的命运。她逃婚来到京城，在游园诗会上偶然结识了心高气傲的肃王徐晋。两人共同经历生死，查明了金器杀人案的真相，抓获了私造兵器的成王徐茂，找出了毒害端妃的真凶。傅容以过人的学识、善良的品格和自强的性格赢得了徐晋的真心爱慕，而徐晋也屡次在危急时刻搭救傅容。在傅容遭遇恩师柳青竹自尽的悲痛时，徐晋鼓励傅容振作起来，一起找出幕后真凶。傅容在赈灾中发现了皇叔徐平的谋反计划，并利用碧玉金簪找到了徐平的密室，最终逼迫徐平自杀伏罪。经历过一系列人生变故之后，傅容和徐晋看淡名利，携手归隐家园，过上了相知相守的幸福生活。Diao Shen Xia: This kind of person may not be limited to running a few demo. He has also made some adjustments to the parameters in the model. No matter whether the adjustment is good or not, he will try it first. Each one will try. If the learning rate is increased, the accuracy rate will decrease. Then he will reduce it. The parameter does not know what it means. Just change the value and measure the accuracy rate. This is the current situation of most junior in-depth learning engineers. Of course, it is not so bad. For Demo Xia, he has made a lot of progress, at least thinking. However, if you ask why the parameter you adjusted will have these effects on the accuracy of the model, and what effects the adjustment of the parameter will have on the results, you will not know again.